code: def selection_r(
      x_bounds,
      x_types,
      clusteringmodel_gmm_good,
      clusteringmodel_gmm_bad,
      num_starting_points=100,
      minimize_constraints_fun=None,
  ):
      """
      Select using different types.
      """
      minimize_starting_points = clusteringmodel_gmm_good.sample(
          n_samples=num_starting_points
      )
  
      outputs = selection(
          x_bounds,
          x_types,
          clusteringmodel_gmm_good,
          clusteringmodel_gmm_bad,
          minimize_starting_points[0],
          minimize_constraints_fun,
      )
  
      return outputs
  
file_path: nni/nni/algorithms/hpo/metis_tuner/Regression_GMM/Selection.py
imports: import os
  import random
  import sys
  from ..None import lib_acquisition_function
  from ..None import lib_constraint_summation
label_desc: Use image node_id 2 for calling a global function with example usage: selection_r(x_bounds, x_types, clusteringmodel_gmm_good, clusteringmodel_gmm_bad, num_starting_points, minimize_constraints_fun) and returns: outputs